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Статті в журналах з теми "Agriculture Simulation Methods"
Volk, Tinea. "Effects of agricultural policy on the development of Slovenian agriculture during the transition and the process of accession to the European Union." Journal of Agricultural Sciences, Belgrade 50, no. 1 (2005): 75–88. http://dx.doi.org/10.2298/jas0501075v.
Повний текст джерелаYamashita, Ryohei. "Dialogue with Different Fields Surrounding Agriculture through the Development of Research using Simulation Methods." Journal of Rural Problems 56, no. 1 (March 25, 2020): 11–16. http://dx.doi.org/10.7310/arfe.56.11.
Повний текст джерелаFibriansari, Rizeki Dwi, Anggia Astuti, and Dwi Ochta Pebriyanti. "IMPROVING MC-KENZIE EXERCISE CAPABILITIES THROUGH SIMULATION METHOD IN THE AGRICULTURE AREA." Jurnal Pengabdian Masyarakat Dalam Kesehatan 4, no. 2 (December 20, 2022): 69–73. http://dx.doi.org/10.20473/jpmk.v4i2.38363.
Повний текст джерелаKiani, Farzad, Amir Seyyedabbasi, Sajjad Nematzadeh, Fuat Candan, Taner Çevik, Fateme Aysin Anka, Giovanni Randazzo, Stefania Lanza, and Anselme Muzirafuti. "Adaptive Metaheuristic-Based Methods for Autonomous Robot Path Planning: Sustainable Agricultural Applications." Applied Sciences 12, no. 3 (January 18, 2022): 943. http://dx.doi.org/10.3390/app12030943.
Повний текст джерелаRadzajewski, Paweł. "Calculation of brake-force distribution on three-axle agricultural trailers using simulation methods." Technical Transactions 2021, no. 1 (2021): 1–18. http://dx.doi.org/10.37705/techtrans/e2021029.
Повний текст джерелаKhoruzhy, Lyudmila Ivanovna, Yury Nikolaevich Katkov, and Anastasiya Alekseevna Romanova. "Modern tools of deep analysis in the system of cost management in inter-organizational relations of agricultural formations." Buhuchet v sel'skom hozjajstve (Accounting in Agriculture), no. 6 (June 1, 2021): 6–15. http://dx.doi.org/10.33920/sel-11-2106-01.
Повний текст джерелаKlose, Steven L., and Joe L. Outlaw. "Financial and Risk Management Assistance: Decision Support for Agriculture." Journal of Agricultural and Applied Economics 37, no. 2 (August 2005): 415–23. http://dx.doi.org/10.1017/s107407080000688x.
Повний текст джерелаPandey, Prateek, Shishir Kumar, and Sandeep Srivastava. "A Critical Evaluation of Computational Methods of Forecasting Based on Fuzzy Time Series." International Journal of Decision Support System Technology 5, no. 1 (January 2013): 24–39. http://dx.doi.org/10.4018/jdsst.2013010102.
Повний текст джерелаSzőke, Szilvia, Lajos Nagy, Sándor Kovács, and Péter Balogh. "Examination of pig farm technology by computer simulation." Applied Studies in Agribusiness and Commerce 3, no. 5-6 (December 30, 2009): 25–29. http://dx.doi.org/10.19041/apstract/2009/5-6/4.
Повний текст джерелаLi, Xiaomin, Lixue Zhu, Xuan Chu, and Han Fu. "Edge Computing-Enabled Wireless Sensor Networks for Multiple Data Collection Tasks in Smart Agriculture." Journal of Sensors 2020 (February 25, 2020): 1–9. http://dx.doi.org/10.1155/2020/4398061.
Повний текст джерелаДисертації з теми "Agriculture Simulation Methods"
Jebari, Asma. "Integrating upscaling simulation methods for predicting soil organic Carbon changes in Spain." Doctoral thesis, Universitat de Lleida, 2022. http://hdl.handle.net/10803/674047.
Повний текст джерелаLa evaluación de stocks de C orgánico del suelo (COS) y emisiones de efecto invernadero (GEI) a escala regional bajo escenarios de cambio climático es de fundamental importancia a la hora de implementar estrategias de manejo para mitigar el cambio climático. El principal objetivo de esta Tesis es evaluar los cambios del COS y GEI en diferentes sistemas agrícolas (e.g., tierras de cultivo y pastos) y diferentes condiciones climáticas (Mediterráneo y templado húmedo) de España bajo diferentes escenarios climáticos. Además, evalué las estrategias de manejo con el objetivo de mitigar los efectos del cambio climático. En el estudio de modelización espacial, se adoptó una versión calibrada del modelo de COS RothC para estimar los cambios en los stocks de COS en condiciones de cambio climático en las tierras de cultivo de la España mediterránea en una superficie total de 23 300 km2 durante el período 2010 a 2100. También simulé las presentes y futuras (2010-2100) emisiones netas para unos 4050 km2 de pastos asociados a la producción lechera de la zona templada húmeda de España. Para la estimación del COS, se modificó el modelo RothC para adaptarlo a los pastos templados húmedos considerando: (1) la incorporación de los diferentes componentes de los residuos vegetales (parte aérea, parte subterránea y rizodeposición) diferenciando su calidad y cantidad, la diferenciación de la calidad de la excreta de los rumiantes, y la extensión de la función de humedad del suelo considerando condiciones de saturación. Para la estimación de los GEI, se usó la metodología refinada del IPCC (Tier 2) considerando emisiones de CH4 and N2O provenientes de la fermentación entérica, del manejo de la excreta y del suelo de los pastos. Según los resultados encontrados en ambos agroecosistemas (es decir, tierras de cultivo y pastos), el cambio climático generalmente condujo a una disminución en el contenido de COS en comparación con los escenarios baseline de referencia. Concluimos que el aporte de C es el factor clave del almacenamiento de COS en las tierras de cultivo mediterráneas y los pastos templados húmedos y que la temperatura del aire es el factor climático que contribuyó más a las variaciones en el COS. Además, la densidad ganadera fue el factor que más afectó a las emisiones netas en los pastos asociados a la producción lechera en el Norte de España. En conclusión, las alternativas de manejo mejoraron la cantidad de COS almacenado y eran estrategias efectivas para reducir las emisiones GEI bajo las condiciones futuras del cambio climático. La siembra directa, en el caso de los cultivos de secano, y la cubierta vegetal, para los olivares y otros cultivos leñosos, fueron las alternativas de manejo eficaces para reducir los efectos del cambio climático y la pérdida de COS. Además, en el caso de pastos templados y húmedos asociados a la producción lechera, las prácticas alternativas de manejo del estiércol (en particular, la digestión anaeróbica) ayudaron a mitigar los efectos del cambio climático y a reducir los GEI netos, mientras que se podría lograr una mayor mitigación mediante la optimización de la densidad ganadera.
Soil organic carbon (SOC) stocks and greenhouse gas (GHG) emissions assessment at the regional scale under climate change scenarios are of paramount importance in implementing management practices to mitigate climate change effect. The main objective of this Thesis was to assess SOC changes and GHG emissions under different agricultural systems (croplands and grasslands) and climatic conditions (Mediterranean and moist temperate) in Spain under different climate scenarios. Furthermore, different alternative management practices to mitigate climate change effects for the considered agroecosystems were also evaluated. A calibrated version of the SOC model RothC was constructed to estimate the changes in SOC under climate change conditions for croplands of Mediterranean Spain across a total surface area of 23 300km2 during the 2010 to 2100 period. It was also simulated current and future (2010–2100) net GHG emissions in more than 4050 km2 of moist temperate Spanish grasslands associated to dairy production under different climate scenarios. For SOC dynamics estimation, the RothC model was modified to fit to managed moist temperate grasslands considering: (1) the incorporation of distinction for plant residues components (i.e., above- and below-ground residues and rhizodeposition) in terms of quantity and quality, (2) ruminant excreta quality, and (3) the extension of soil moisture up to saturation conditions. For GHG estimation, it was used mainly Tier 2 IPCC methodologies to estimate the CH4 and N2O emissions from enteric fermentation, manure storage and handling, and grassland soils. According to my findings, among both agroecosystems (i.e., croplands and grasslands), climate change generally led to a decline in SOC content compared with baseline scenarios. Furthermore, C input was the key factor of SOC storage across Mediterranean croplands and moist temperate Spanish grasslands. Additionally, it was found that air temperature rather than precipitation was the climatic factor contributing to most of variation in SOC changes values. Moreover, livestock density was the main factor affecting net GHG emissions in the grasslands associated to dairy production of Northern Spain. It was concluded that changes in management could enhance the amount of SOC sequestered and reduce GHG emissions under climate change conditions. Under Mediterranean croplands, no-tillage, in the case of rainfed crops, and vegetation cover, for olive groves and other woody crops, were the alternative management strategies to alleviate climate change effects and SOC loss. In addition, under moist temperate grassland-based dairy livestock systems, alternative manure management practices (particularly, anaerobic digestion) were efficient to mitigate the climate change effects and to reduce the net GHG emissions, while more mitigation could be achieved by optimising the livestock density management.
Schmidt, Darren John. "Introducing crop simulation technology using soft systems methodology : some issues in agricultural communication." Thesis, Queensland University of Technology, 1994. https://eprints.qut.edu.au/36401/1/36401_Schmidt_1994.pdf.
Повний текст джерелаBorodin, Valeria. "Optimisation et simulation d'une chaîne logistique : application au secteur de l'agriculture." Thesis, Troyes, 2014. http://www.theses.fr/2014TROY0034/document.
Повний текст джерелаTo overcome the new challenges facing agricultural sector, imposed by globalisation, changing market demands and price instability, the crop production supply chain must particularly be very reactive, flexible, with a high yield and at low cost. Its improving and eventual re-configuration can lead to an upgrade in efficiency, responsiveness, business integration and make it able to confront the market competitiveness. The thesis is thus placed in this particular context and aims to support decision making in crop harvesting activity, which is considered the pivotal stage in the cereal production circuit owing to its high cost and impact on the returns earned. Managing the harvest activity involves gathering, transportation and storage operations, performed by a collection of agricultural holdings geographically dispersed. Besides its practical relevance, this thesis forms part of the Operational Research (OR) and more specifically, refers to the linear and stochastic programming, discrete event simulation, and their coupling. In addition, the synergy created between OR, inferential and predictive statistics, geographical information system tools makes the decision support system competitive, efficient and responsive
Marinelli, Marco Antonio. "Modelling and communicating the effects of spatial data uncertainty on spatially based decision-making." Thesis, Curtin University, 2011. http://hdl.handle.net/20.500.11937/1842.
Повний текст джерелаPopiolek, Nathalie. "Modèle prospectif de consommation d'énergie dans l'agriculture : le cas de la fertilisation azotée a l'horizon 2010." Grenoble 2, 1993. http://www.theses.fr/1993GRE21027.
Повний текст джерелаThe first part of this thesis gives a critical overview of available forecasting methods. After this survey, the methodology chosen for the construction of the model is presented. This construction constitutes the second stage of this work. The "energy and nitrogen fertilization" system is defined (list of key variables for its evolution towards the year 2010 and analysis of their relationships) and then modelized highlighting the nitrogen fertilizers demand. The demand is determined for the year 2010 by the mean of a linear programming model (aropaj) based on farmers' cropping choices. This model, first used for short and middle terms is adapted for the long term (2010) by using peripheral models projecting the fixed factors (in the short term) of agricultural holdings and their way of producing. These projections are based on experts inquiries (delphi) constitutes the third part of this thesis. These scenarios constitute the patterns of simulation running on the linear programme to test the impact of the future common agricultural policy or the introduction of technological innovations
Haned, Hinda. "Évaluation de méthodes statistiques pour l'interprétation des mélanges d'ADN en science forensique." Phd thesis, Université Claude Bernard - Lyon I, 2010. http://tel.archives-ouvertes.fr/tel-00817181.
Повний текст джерелаHalama, Tadeáš. "Pevnostní analýza a optimalizace nosiče výměnných nástaveb MEGA 25." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2017. http://www.nusl.cz/ntk/nusl-318666.
Повний текст джерелаSharma, Sunil Kumar. "A comparison of combinatory methods and GIS based MOLA (IDRISI®) for solving multi-objective land use assessment and allocation problems." Phd thesis, 2005. http://hdl.handle.net/1885/12855.
Повний текст джерелаSulistyawati, Endah. "An agent-based simulation of land-use in a swidden agricultural landscape of the Kantu' in Kalimantan, Indonesia." Phd thesis, 2001. http://hdl.handle.net/1885/146045.
Повний текст джерела(8800949), Patrick N. Maier. "A Bioeconomic Model of Indoor Pacific Whiteleg Shrimp (Litopenaeus Vannamei) Farms With Low-Cost Salt Mixtures." Thesis, 2020.
Знайти повний текст джерелаКниги з теми "Agriculture Simulation Methods"
Simulation and systems analysis in agriculture. Amsterdam: Elsevier, 1985.
Знайти повний текст джерелаRoningen, Vernon. A Static World Policy Simulation (SWOPSIM) modeling framework. [Washington, D.C.]: U.S. Dept. of Agriculture, Economic Research Service, International Economics Division, 1986.
Знайти повний текст джерелаFlichman, Guillermo. Bio-economic models applied to agricultural systems. Dordrecht: Springer, 2011.
Знайти повний текст джерелаElderen, E. Van. Scheduling farm operations: A simulation model. Wageningen, Netherlands: Pudoc, 1987.
Знайти повний текст джерелаHuang, Barney K. Computer simulation analysis of biological and agricultural systems. Boca Raton, FL: CRC Press, 1994.
Знайти повний текст джерелаDukes, Richard L. Worlds apart: Collective action in simulated agrarian and industrial societies. Dordrecht: Kluwer Academic, 1990.
Знайти повний текст джерелаBrouwer, Floor. Environmental and agricultural modelling: Integrated approaches for policy impact assessment. Dordrecht: Springer, 2010.
Знайти повний текст джерелаHertel, Thomas W. Adding value to existing models of international agricultural trade. [Washington, DC]: U.S. Dept. of Agriculture, Economic Research Service, 1994.
Знайти повний текст джерелаJonathan, Kydd, Maetz Materne, Heath Julia, and Food and Agriculture Organization of the United Nations., eds. Southland: A case study-based training exercise in policy analysis for the agricultural and rural sector. Rome: Food and Agriculture Organization of the United Nations, 2003.
Знайти повний текст джерелаNIES Workshop on Information Bases and Modeling for Land-Use and Land-Cover Changes Studies in East Asia (1999 Tsukaba, Japan). Proceedings of 1999 NIES Workshop on Information Bases and Modeling for Land-Use and Land-Cover Changes Studies in East Asia. Ibaraki, Japan: Center for Global Environmental Research, National Institute for Environmental Studies, Environment Agency of Japan, 1999.
Знайти повний текст джерелаЧастини книг з теми "Agriculture Simulation Methods"
Rueda, J. L., C. Leon-Velarde, T. Walker, and H. Zandstra. "CIP’s experiences in the use of systems analysis and simulation." In Opportunities, use, and transfer of systems research methods in agriculture to developing countries, 289–94. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0762-4_24.
Повний текст джерелаRueda, J. L., C. Leon-Velarde, T. Walker, and H. Zandstra. "CIP’s experiences in the use of systems analysis and simulation." In Opportunities, use, and transfer of systems research methods in agriculture to developing countries, 289–94. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0764-8_19.
Повний текст джерелаZhao, Peng-fei, Tian-en Chen, Wei Wang, and Fang-yi Chen. "Research on Plant Growth Simulation Method Based on ARToolkit." In Computer and Computing Technologies in Agriculture X, 189–96. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-06155-5_18.
Повний текст джерелаHusain, Saiful Azmi, and Nor Hamizah Mohd Rhyme. "Decision Support Method for Agricultural Irrigation Scenarios Performance Using WEAP Model." In Theoretical, Modelling and Numerical Simulations Toward Industry 4.0, 99–106. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8987-4_7.
Повний текст джерелаHuang, Peichen, Xiwen Luo, and Zhigang Zhang. "Headland Turning Control Method Simulation of Autonomous Agricultural Machine Based on Improved Pure Pursuit Model." In Computer and Computing Technologies in Agriculture III, 176–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12220-0_27.
Повний текст джерелаAdiku, S. G. K., L. R. Ahuja, G. H. Dunn, J. D. Derner, A. A. Andales, L. Garcia, and P. N. S. Bartling. "Parameterization of the GPFARM-Range Model for Simulating Rangeland Productivity." In Methods of Introducing System Models into Agricultural Research, 209–28. Madison, WI, USA: American Society of Agronomy and Soil Science Society of America, 2015. http://dx.doi.org/10.2134/advagricsystmodel2.c7.
Повний текст джерелаJabro, Jay D., John L. Hutson, and Ann D. Jabro. "Parameterizing LEACHM Model for Simulating Water Drainage Fluxes and Nitrate Leaching Losses." In Methods of Introducing System Models into Agricultural Research, 95–115. Madison, WI, USA: American Society of Agronomy and Soil Science Society of America, 2015. http://dx.doi.org/10.2134/advagricsystmodel2.c3.
Повний текст джерелаWu, Ding-feng, Guo-min Zhou, Jian Wang, and Jian Wang. "Research on the Method of Simulating Knowledge Structure of the Information Searchers — Illustrated by the Case of Pomology Information Retrieval." In Computer and Computing Technologies in Agriculture VII, 450–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54344-9_51.
Повний текст джерелаLezhenkin, Oleksandr, Ivan Lezhenkin, Oleksandr Vershkov, and Serhii Kolomiiets. "Simulation of Cereal Crops Harvesting Using the Method of Grain Crops Combing in Standing Position in Conditions of Farming Enterprises." In Modern Development Paths of Agricultural Production, 91–98. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14918-5_10.
Повний текст джерелаCarter, Timothy R., and Stefan Fronzek. "A Model-Based Response Surface Approach for Evaluating Climate Change Risks and Adaptation Urgency." In Springer Climate, 67–75. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-86211-4_9.
Повний текст джерелаТези доповідей конференцій з теми "Agriculture Simulation Methods"
Lu, Ling, Weng-lin Song, and Lei Wang. "A simulation method for the fruitage body." In International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009). SPIE, 2009. http://dx.doi.org/10.1117/12.836947.
Повний текст джерелаRyan, Sydney D., Andrew G. Gerber, Gorden A. L. Holloway, and Ali Bagherpour. "Computational Study of Aerial Sprays Used for Forest Protection." In ASME 2010 3rd Joint US-European Fluids Engineering Summer Meeting collocated with 8th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2010. http://dx.doi.org/10.1115/fedsm-icnmm2010-30270.
Повний текст джерелаGao, GuoHua, XuBo Wang, Tao Ding, ZiHua Zhang, and JinFeng Wei. "Research on agricultural equipment design method based on MBSE." In International Conference on Mechanical Design and Simulation (MDS 2022), edited by Dongyan Shi and Guanglei Wu. SPIE, 2022. http://dx.doi.org/10.1117/12.2638727.
Повний текст джерелаBorghesi, Giulia, and Giuseppe Vignali. "Life cycle assessment of organic Parmesan Cheese considering the whole dairy supply chain." In The 5th International Food Operations & Processing Simulation Workshop. CAL-TEK srl, 2019. http://dx.doi.org/10.46354/i3m.2019.foodops.004.
Повний текст джерелаRen, Haifeng, and Yansheng Song. "A New 3D Crack Simulation Method of High Pressure Rubber Hose Pipe." In 2021 International Conference on Electronic Information Technology and Smart Agriculture (ICEITSA). IEEE, 2021. http://dx.doi.org/10.1109/iceitsa54226.2021.00073.
Повний текст джерелаXiaogang Wang, V. E. Kuzmichev, Yun Luo, and Yue Li. "A garment simulating method based on scanning technology." In 2010 International Conference On Computer and Communication Technologies in Agriculture Engineering (CCTAE). IEEE, 2010. http://dx.doi.org/10.1109/cctae.2010.5544116.
Повний текст джерелаLi, J., Z. H. Zhou, J. J. Liu, and H. Wang. "The simulation methods and application on agricultural nonpoint source pollution: a review." In International Conference on Environmental Science and Biological Engineering. Southampton, UK: WIT Press, 2014. http://dx.doi.org/10.2495/esbe140911.
Повний текст джерелаLi Chunqing, Li Xingman, and Wang Tao. "Notice of Retraction: Research on MBR modeling and simulation achieved by the least square method." In 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering (CCTAE 2010). IEEE, 2010. http://dx.doi.org/10.1109/cctae.2010.5544232.
Повний текст джерелаPayungsak Junyusen and Tomohiro Takigawa. "Simulation of a Steering Aid Method for an Agricultural Tractor-Trailer System." In 2010 Pittsburgh, Pennsylvania, June 20 - June 23, 2010. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2010. http://dx.doi.org/10.13031/2013.29711.
Повний текст джерелаYang, Yan-min, Yonghui Yang, Shu-min Han, and Yu-kun Hu. "Simulation of temporal and spatial distribution of required irrigation water by crop models and the pan evaporation coefficient method." In International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009). SPIE, 2009. http://dx.doi.org/10.1117/12.836674.
Повний текст джерелаЗвіти організацій з теми "Agriculture Simulation Methods"
Shani, Uri, Lynn Dudley, Alon Ben-Gal, Menachem Moshelion, and Yajun Wu. Root Conductance, Root-soil Interface Water Potential, Water and Ion Channel Function, and Tissue Expression Profile as Affected by Environmental Conditions. United States Department of Agriculture, October 2007. http://dx.doi.org/10.32747/2007.7592119.bard.
Повний текст джерелаMiles, Gaines E., Yael Edan, F. Tom Turpin, Avshalom Grinstein, Thomas N. Jordan, Amots Hetzroni, Stephen C. Weller, Marvin M. Schreiber, and Okan K. Ersoy. Expert Sensor for Site Specification Application of Agricultural Chemicals. United States Department of Agriculture, August 1995. http://dx.doi.org/10.32747/1995.7570567.bard.
Повний текст джерелаPullammanappallil, Pratap, Haim Kalman, and Jennifer Curtis. Investigation of particulate flow behavior in a continuous, high solids, leach-bed biogasification system. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600038.bard.
Повний текст джерелаShmulevich, Itzhak, Shrini Upadhyaya, Dror Rubinstein, Zvika Asaf, and Jeffrey P. Mitchell. Developing Simulation Tool for the Prediction of Cohesive Behavior Agricultural Materials Using Discrete Element Modeling. United States Department of Agriculture, October 2011. http://dx.doi.org/10.32747/2011.7697108.bard.
Повний текст джерелаLaw, Edward, Samuel Gan-Mor, Hazel Wetzstein, and Dan Eisikowitch. Electrostatic Processes Underlying Natural and Mechanized Transfer of Pollen. United States Department of Agriculture, May 1998. http://dx.doi.org/10.32747/1998.7613035.bard.
Повний текст джерелаZhang, Renduo, and David Russo. Scale-dependency and spatial variability of soil hydraulic properties. United States Department of Agriculture, November 2004. http://dx.doi.org/10.32747/2004.7587220.bard.
Повний текст джерелаCrowley, David E., Dror Minz, and Yitzhak Hadar. Shaping Plant Beneficial Rhizosphere Communities. United States Department of Agriculture, July 2013. http://dx.doi.org/10.32747/2013.7594387.bard.
Повний текст джерелаWarrick, Arthur W., Gideon Oron, Mary M. Poulton, Rony Wallach, and Alex Furman. Multi-Dimensional Infiltration and Distribution of Water of Different Qualities and Solutes Related Through Artificial Neural Networks. United States Department of Agriculture, January 2009. http://dx.doi.org/10.32747/2009.7695865.bard.
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